Viewing stemming as recall enhancement
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
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As the number of published documents increase quickly, there is a crucial need for fast and sensitive categorization methods to manage the produced information. In this paper, we focused on the categorization of biomedical documents with concepts of the Gene Ontology, an ontology dedicated to gene description. Our approach discovers associations between the predefined concepts and the documents using string matching techniques. The assignations are ranked according to a score computed given several strategies. The effects of these different scoring strategies on the categorization effectiveness are evaluated. More especially a new weighting technique based on term frequency is presented. This new weighting technique improves the categorization effectiveness on most of the experiment performed. This paper shows that a cleaver use of the frequency can bring substantial benefits when performing automatic categorization on large collection of documents.